Through public data made available by John Hopkins University, it was possible to build a graph of the evolution of the virus over the days in South America and the European Community, with the first cases reported in America in early March, and those of the Europe only 10 days before.
The charts below are iterative, it is possible to include and exclude countries in their visualization, zoom in/out on specific points of it and drag the axes; besides being able to visualize the precise figures by hovering over the curve.
I am not an infectious disease specialist, far from it. The charts show by themselves. Each person make their own conclusions.
Each chart of the macro-political regions, the worst-off country on the other side was included too, in order to facilitate the comparison. This curve, at first, is turned off; just click on the legend that it becomes available.
Due the exponential growth of the curves it is known that the uncertanties on a prediction are substancial; however, no predictive machine learning algorithm is necessary to conclude that in about a week South American countries, specially in Brazil, can be in an extreme bad mood if irresponsible attitudes were taken.
As a tool, among the several advantages of the Python programming language, I highlight the robustness in data manipulation and visualization, as presented in this article.